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Osronita Osronita
Program Studi Geografi Universitas Tamansiswa Padang
Earth & Planetary Sciences Environmental Science Social Sciences

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PENENTUAN KERAWANAN BENCANA LONGSOR BERBASIS GIS DI KABUPATEN PESISIR SELATAN Resti Islami Putri; Novelisa Suryani; Osronita Osronita
Jurnal Azimut Vol 5 No 2 (2023)
Publisher : Universitas Tamansiswa Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31317/jaz.v5i2.850

Abstract

The purpose of this study was to determine the distribution of landslide-prone areas and evaluate the suitability of spatial patterns based on landslide vulnerability in Pesisir Selatan Regency. The method is quantitative and descriptive using score classification and parameter weighting used, based on the Puslittanak method (2004). To evaluate the suitability of an area's spatial pattern for landslide hazard using a GIS-based overlay method (ArcGIS 10.3 software). Based on the results of the study, it can be concluded that the Pesisir Selatan region has a low landslide vulnerability of 125788,3 ha (21%), a moderate landslide vulnerability of 455685,8 ha (76%), covering 15 sub-districts, and a high. prone to landslides covering an area of 20293 ha (3%) covering 14 districts. The landslide susceptibility map shows 67% suitable and 33% not suitable. Suitable are advised not to carry out new developments or expansion of land use, and areas that are not suitable need to revise regional spatial patterns, especially in areas prone to high landslides.
POTRET GEOGRAFIS KEMISKINAN DI PROVINSI BENGKULU: KOMPARATIF KEMISKINAN WILAYAH UTARA DAN SELATAN Rihan Ifebri; Reflis Reflis; Ellys Yuliarti; Sriyoto Sriyoto; Osronita Osronita
Jurnal Azimut Vol 5 No 2 (2023)
Publisher : Universitas Tamansiswa Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31317/jaz.v5i2.953

Abstract

Multidimensional poverty research was carried out in districts/cities located in the coastal area of ??Bengkulu Province. This research aims to identify the intensity of poverty, identify multidimensional poverty, and identify the level of poverty deprivation in districts/cities in the coastal areas of Bengkulu Province. This research uses secondary data from the Central Statistics Agency (BPS) of Bengkulu Province in the form of microstatistical data, namely National Socio-Economic Survey (SUSENAS) pooled cross-section data with a survey wave period of 2022. The method used is the Multidimensional Poverty Index (MPI) method. modified from Alkire and Foster. The results of the research show that the intensity of multidimensional poverty in the northern region, namely the Muko-Muko district (15.28%) is lower than in the southern region, namely the Kaur district (37.16%). The Multidimensional poverty rate (M) in the Northern region of Bengkulu Province, namely Muko-Muko Regency, is smaller (6.16%) compared to the Southern region of Bengkulu Province, namely Kaur Regency (16.98%). Household deprivation status according to multidimensional poverty indicators, namely the number of years of schooling, potable water, and then the indicators of household calorie consumption and household protein consumption which contribute a lot to multidimensional poverty in the Northern region of Bengkulu Province, namely Muko-Muko Regency and the Southern Region of Bengkulu Province, namely Kaur District.
Co-Authors Ellys Yuliarti Novelisa Suryani Reflis Reflis Resti Islami Putri Rihan Ifebri Sriyoto Sriyoto